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| Presentation | 2019-04-19 11:20 A Study on DOA Estimation Using Deep Learning Yuya Kase, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa (Hokkaido Univ.), Daisuke Kitayama, Yoshihisa Kishiyama (NTT DOCOMO)  RCS2019-17 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Direction of arrival (DOA) estimation of radio waves is applicable to localization of users in mobile communication and radar systems. In addition to MUSIC and ESPRIT, which are well-known traditional algorithms, compressed sensing has been applied to DOA estimation with the development of computing resources. Although compressed sensing requires larger computational load, it has a higher accuracy compared with MUSIC in general. If such a large computational load is acceptable, it is expected that we can obtain the higher estimation accuracy by applying deep learning. In this paper, we consider an estimation method using deep learning and examine its characteristics in the case where two narrow-band signals impinge on a linear array. The simulation results show that high estimation accuracy comparable to MUSIC is obtained and that the performance highly depends on the training parameters. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | DOA estimation / array antenna / deep learning / deep neural network / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 8, RCS2019-17, pp. 79-84, April 2019. | |
| Paper # | RCS2019-17 | |
| Date of Issue | 2019-04-11 (RCS) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | RCS2019-17 |
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| Conference Information | |
| Committee | RCS |
| Conference Date | 2019-04-18 - 2019-04-19 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Noboribetsu Grand Hotel |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Railroad Communications, Inter-Vehicle Communications, Road to Vehicle Communications, Radio Access Technologies, Wireless Communications, etc. |
| Paper Information | |
| Registration To | RCS |
| Conference Code | 2019-04-RCS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study on DOA Estimation Using Deep Learning |
| Sub Title (in English) | |
| Keyword(1) | DOA estimation |
| Keyword(2) | array antenna |
| Keyword(3) | deep learning |
| Keyword(4) | deep neural network |
| Keyword(5) | |
| Keyword(6) | |
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| Keyword(8) | |
| 1st Author's Name | Yuya Kase |
| 1st Author's Affiliation | Hokkaido University (Hokkaido Univ.) |
| 2nd Author's Name | Toshihiko Nishimura |
| 2nd Author's Affiliation | Hokkaido University (Hokkaido Univ.) |
| 3rd Author's Name | Takeo Ohgane |
| 3rd Author's Affiliation | Hokkaido University (Hokkaido Univ.) |
| 4th Author's Name | Yasutaka Ogawa |
| 4th Author's Affiliation | Hokkaido University (Hokkaido Univ.) |
| 5th Author's Name | Daisuke Kitayama |
| 5th Author's Affiliation | NTT DOCOMO, INC. (NTT DOCOMO) |
| 6th Author's Name | Yoshihisa Kishiyama |
| 6th Author's Affiliation | NTT DOCOMO, INC. (NTT DOCOMO) |
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| Speaker | Author-1 |
| Date Time | 2019-04-19 11:20:00 |
| Presentation Time | 25 minutes |
| Registration for | RCS |
| Paper # | RCS2019-17 |
| Volume (vol) | vol.119 |
| Number (no) | no.8 |
| Page | pp.79-84 |
| #Pages | 6 |
| Date of Issue | 2019-04-11 (RCS) |
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